Last year, fashion publications wrote extensively about the impact of the algorithm on personal style. (Vogue Business included.)
The algorithm — shorthand for data-influenced recommendations — is making discovery harder. It’s killing personal style. It’s a positive for Gen Z. It’s a catalyst for the surge in fast fashion and overconsumption. It’s avoidable — just look at Substack. It’s supercharged micro-trends. It’s killed them. The list goes on.
In last year’s fashion conversation, ‘the algorithm’ surpassed its status as an opaque operator worth interrogating for how it’s shaping what we see online. It evolved into a catch-all card to pull out at any mention of sameness, like a lack of creativity or personal style. The algorithm is what we’ve come to blame for wider industry issues and frustrations, many of which are driven by economic and cultural shifts outside of the tech’s purview entirely. In the process, has it become a crutch?
“It’s lazy,” says Shaun Singh, founder and CEO of trend media company Death to Stock (DTS). “It’s a vague, convenient villain we use to avoid harder conversations about inequity, control and transparency in the fashion industry. [In] 2025, we should be talking less about algorithms and more about the systems they support.”
On the flip side, algorithmic recommendations do indeed influence what consumers see, covet and buy, including what becomes a trend and what doesn’t. “There is a component of a consumer having always coveted the same trending items, but the algorithm has accelerated that and taken it to a new, much faster paced level,” says luxury fashion sourcer Gab Waller, who pinpoints TikTok’s infamous algorithm as the key driver of what her clients are requesting.
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It’s a case of chicken and egg: TikTokers wear similarly styled looks with the same (or similar) pieces; said looks get eyeballs; this drives sales; designers create similar output to these existing looks; these, once again, pop up online for creators to style and wear. Where it begins is fuzzy. But what’s clear is audiences are growing tired of this repetition.
“We’re reaching a tipping point where audiences — and creators — are tiring of algorithmic sameness,” Singh says. “Fashion brands have an opportunity to stand out by resisting the urge to optimise for engagement and instead leaning into risk and individuality.”
Brands are responsible for switching up their input — how they feed the machine. But it’s also up to both industry insiders and fashion audiences to reassess what’s driving trends and personal style beyond the elusive algorithm. Because it doesn’t start there.
Pandering to the machine
Algorithms have shifted from trend amplifiers to dictators, says Singh. TikTok is, by and large, to thank. “My algorithm is just too good,” 25-year-old content creator Tora Northman told Vogue Business last year, citing TikTok as her go-to platform for discovery. She’s not alone — 70 per cent of Gen Zs say online discovery has gotten easier, and 48 per cent have positive sentiment towards algorithmic recommendations, per Vogue Business’s survey on the topic.
For Waller’s part, TikTok is her clients’ leading source of discovery. “It is more common now to receive a screenshot from TikTok than from Instagram or any other social media channel,” she says of how clients share what they’re looking for. Client requests begin creeping in once they see a given piece featured on numerous creators, Waller says. “A trending item isn’t often immediate. It takes the client seeing it numerous times before they jump on — and the trend kicks off.”
It’s a blessing and a curse. “The danger of the algorithm is that it cannot make generative decisions for you, it can only make decisions based on what you tell it about you,” says fashion commentator and Substack author Tariro Makoni. Most users consume content passively, meaning they’re unlikely to receive content outside of what they’re already interested in, and are therefore unable to discover or hone new and different tastes. “If you’re passively consuming, and not actively trying to bait your algorithm to show you something outside of who it perceives you to be, you’re stuck in sameness,” Makoni says.
So it’s no wonder brands’ product outputs (which turn into their algorithmic inputs) are starting to look alike. This passive consumption means almost everyone is interacting with the same baggy jeans and boxy white tee, Makoni says — a basic, palatable combo that suits many different feeds. This means data on what consumers want is driven by the content consumers are viewing en masse — not what may be sitting in the fringes of their algorithms, she explains. This results in what Makoni calls a “singularity of consumption”.
As a US TikTok ban becomes a very real possibility, it leaves an interesting white space, she continues. “No algo is as sophisticated as theirs,” Makoni says. In the absence of TikTok’s razor-sharp algorithmic output, fashion may well be pushed to think beyond algorithmically defined, quick-hit trends and looks. Singh agrees: “Without TikTok’s magic, these [micro-trends] might slow, forcing brands and creators to rethink their dependence on fleeting aesthetics.”
Scapegoating ‘the algorithm’
But is the algorithm really to blame for the flattening of aesthetics — and subsequent obsession with the hunt for personal style — that we saw last year? Not solely.
“The industry loves to scapegoat ‘the algorithm’ for its own lack of imagination,” Singh says. “Algorithms don’t demand fast fashion or exploitative practices — brands do. Algorithms simply amplify what they’re fed. If the system feels broken, it’s because the industry prioritised convenience and scale over quality and innovation long before algorithms entered the picture.”
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Singh attributes the industry pushback to a loss of control. “Fashion used to have gatekeepers who dictated trends from the top down. Now, it’s the crowd — or rather, the algorithm — shaping the crowd,” he says. “The problem isn’t algorithms; it’s that the industry hasn’t figured out how to lead in an age where control is shared.”
For brands, the answer isn’t just to feed the algorithm, which Singh says is a race to the bottom. “Instead, fashion must consider where it can create its own spaces — platforms or communities where designers and creators set the rules,” he says. “If algorithm-driven platforms are here to stay, the question isn’t how to play their game but how to redefine it. Could fashion shift its focus from playing within these platforms to building ecosystems that exist outside of them?”
Even on-platform, though, brands can switch course. “Brands and those in the business of curation (tastemakers, editors, publications) should spend more time ideating what they want the majority of their inputs to be. Almost similar to how print magazines used to influence culture,” Makoni says. “The difference is that the volume of interactions will determine what rises to the top, almost instantly.”
This goes back to the idea of shared control — and it’s a concept brands and industry leads need to work with, rather than against, experts agree. “This new, instantaneous model is somewhat meritocratic, and a good way to think about the bi-directional funnel between influence, consumption and the dissemination of trends and ideas across culture,” Makoni says.
Just like we need to continue interrogating those in the top roles at brands, influencing their output, we ought to remain aware and critical of the technology that shapes our engagement with fashion. But, as an industry, we also must be hyper-aware of what is a result of algorithmic recommendations, and what we ourselves are feeding the algorithm. It’s not all down to the tech.
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